A sufficiently fast algorithm for finding close to optimal junction trees

Authors:
Ann Becker;Dan Geiger
Affiliations:
Computer Science Department Technion, Haifa, Israel;Computer Science Department Technion, Haifa, Israel
Venue:
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Year:
1996

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Abstract

Au algorithm is developed for findiug a close to optimal junction tree of a given graph G. The algorithm has a worst case complexity O(ckna) where a and c are constants, n is the nmnber of vertices, and k is the size of the largest clique in a juuction tree of G in which this size is minimized. The algorithm guarantees that the logarithm of the size of the state space of the heaviest clique in the junction tree produced is less than a constant factor off the optional value. When k = O(log n) our algorithm yields a polynomial inference algorithm for Bayesian networks.